code: def test_pytorch_convert_inputs(data, n_args, kwargs_keys):
      import torch.nn
  
      model = PyTorchWrapper(torch.nn.Linear(3, 4))
      convert_inputs = model.attrs["convert_inputs"]
      Y, backprop = convert_inputs(model, data, is_train=True)
      check_input_converters(
          Y, backprop, data, n_args, kwargs_keys, torch.Tensor
      )
  
file_path: thinc/thinc/tests/layers/test_pytorch_wrapper.py
imports: import numpy
  import pytest
  from thinc.api import SGD, ArgsKwargs, CupyOps, Linear, MPSOps, NumpyOps, PyTorchWrapper, PyTorchWrapper_v2, PyTorchWrapper_v3, Relu, chain, get_current_ops, torch2xp, use_ops, xp2torch
  from thinc.backends import context_pools
  from thinc.compat import has_cupy_gpu, has_torch, has_torch_amp, has_torch_mps_gpu
  from thinc.layers.pytorchwrapper import PyTorchWrapper_v3
  from thinc.shims.pytorch import default_deserialize_torch_model, default_serialize_torch_model
  from thinc.shims.pytorch_grad_scaler import PyTorchGradScaler
  from thinc.util import get_torch_default_device
  from ..util import check_input_converters, make_tempdir
label_desc: Use image node_id 7 for calling a global function with example usage: test_pytorch_convert_inputs(data, n_args, kwargs_keys) without return types